Lloyd–Max's Algorithm Implementation in Speech Coding Algorithm Based on Forward Adaptive Technique

The posterior vermis of the cerebellum is considered to be critically involved in saccadic adaptation. However, recent evidence suggests that the adaptive decrease (backward adaptation) and the adaptive increase (forward adaptation) of saccade amplitude rely on partially separate neural substrates. We investigated whether the posterior cerebellum could be differentially involved in backward and forward adaptation by using transcranial direct current stimulation (TDCS). To do so, participants' saccades were adapted backward or forward while they received anodal, cathodal, or sham TDCS. In two extra groups, subjects underwent a nonadaptation session while receiving anodal or cathodal TDCS to control for the direct effects of TDCS on saccadic execution. Surprisingly, cathodal stimulation tended to increase the extent of both forward and backward adaptations, while anodal TDCS strongly impaired forward adaptation and, to a smaller extent, backward adaptation. Forward adaptation was accompanied by a greater increase in velocity with cathodal stimulation, and reduced duration of change for anodal stimulation. In contrast, the expected velocity decrease in backward adaptation was noticeably weaker with anodal stimulation. Stimulation applied during nonadaptation sessions did not affect saccadic gain, velocity, or duration, demonstrating that the reported effects are not due to direct effects of the stimulation on the generation of eye movements. Our results demonstrate that cerebellar excitability is critical for saccadic adaptation. Based on our results and the growing evidence from studies of vestibulo-ocular reflex and saccadic adaptation, we conclude that the plasticity at the level of the oculomotor vermis is more fundamentally important for forward adaptation than for backward adaptation.

This paper presents a simple differential speech signal coding algorithm, based on backward adaptation. The considered algorithm is executed in frame by frame manner, by implementing predictive and adaptive quantization techniques. Both prediction and adaptation are performed backward, based on the previously quantized input signal frame. This enables us to obtain high quality output signal, without increasing the bit rate. This research puts emphasis on the quantizer design, with the optimal support limit determination, and theoretical performance evaluation. Objective quality of the output signal is evaluated through signal to quantization noise ratio (SQNR). We perform theoretical and experimental analysis of the algorithm performance and provide comparative results of implementing speech signal coding techniques with similar complexity. Experimental results show that our simple differential speech coding algorithm satisfies the G.712 Recommendation for high-quality speech coding at the bit rate of 6 bits per sample. This indicates that the algorithm can be successfully implemented in high quality speech signal coding.

Simulation results are presented which compare the performance of all-pole, all-zero, and pole-zero predictors in ADPCM at data rates of 16 and 32 kbits/s over both ideal and noisy channels. Separate backward adaptive gradient algorithms are used to adapt the poles and the zeros independently. The performance indicators used are signal-to-quantization noise ratio (SNR), signal-to-prediction error ratio (SPER), segmental SNR (SNRSEG), and subjective listening tests. For speech sources, the all-zero and pole-zero predictors produce SNR and SNRSEG values that are approximately 1-3 dB higher than those generated by the all-pole predictor. Subjective listening tests reveal that an eighth-order all-zero predictor performs as well or better than an allpole predictor for all conditions studied.

Usually, the performance of a low-bit-rate speech coder degrades seriously in the presence of various interfering signals such as the background noise, acoustic echo, co-talkers' speech and other unwanted signals. This comes from the mismatch between the input signal and the assumed speech production model on which the design of the given speech coder is based. In this paper, we present an approach to modify the input signal such that it can be coded more effectively within the generalized analysis-by-synthesis framework. Signal modification in the presented approach is performed according to a criterion which makes a compromise between the modification and coder quantization errors. The coder-decoder (CODEC) characteristic is described in terms of a transfer matrix, and an on-line method using the recursive least square (RLS) technique is proposed to estimate it. Since each part of the speech signal is differently affected by the modification, we also devise an adaptive method based on the signal-to-quantization noise ratio (SQNR). In contrast to the conventional modification techniques, our approach can be implemented as a simple front-end for any analysis-by-synthesis type coders.

Recent advances in speech coding algorithms and techniques based on the use of linear prediction now permit high quality voice reproduction at remarkably low bit rates. This paper reviews some of the main ideas underlying the algorithms of major interest today. The concept of removing redundancy by linear prediction is reviewed, first in the context of predictive quantization or DPCM. Then linear predictive coding, adaptive predictive coding, and vector quantization are discussed. The concepts of excitation coding via analysis-by-synthesis linear predictive coding is explained and some important enhancements such as vector sum excitations, and adaptive postfiltering are described. Low-delay coding by backward computation of LPC parameters is explained. The concept of phonetic segmentation of speech for closed-loop coding systems is also presented. Linear prediction is the key technique that underlies almost all of the important algorithms for speech coding of interest today. Finally, we discuss some recent work on nonlinear prediction of speech and its potential for the future of speech coding.

In this paper, we propose a novel algorithm to design an optimal non-uniform scalar quantizer for distributed video coding, which aims at achieving a coding rate close to joint conditional entropy of the quantized video frames given the side information. Wyner-Ziv theory on source coding is employed as the basic coding principle and the asymmetric scenario is considered. In this algorithm, a probability distribution model, which considers the influence of the joint distribution of input source and side information to the coding performance, is established and used as the optimality condition firstly. Then, a modified Lloyd Max algorithm is used to design the scalar quantizer to give an optimal quantization for input source before coding. Experimental results show that compared to uniform scalar quantization, proposed algorithm can improve coding performance largely, especially at low bit rate

To attain a very-low-delay speech coder at 16 kb/s while maintaining a quality acceptable for the public switched telephone network, low delay vector excitation coding (LD-VXC) is introduced. Backward adaptation is used to track the spectral characteristics of the signal without requiring any buffering of the input speech, thereby allowing a very low delay to be achieved in an analysis-by-synthesis structure. The algorithm differs markedly from conventional VXC or CELP (code-excited linear prediction) coders due to the use of backward adaptive linear prediction for modeling the time-varying short- and long-term correlation of speech. The LD-VXC coder provides very good speech quality at 16 kb/s, moderate complexity, a delay of under 2 ms, and a gentle degradation of quality with transmission errors. The algorithm was submitted to the CCITT as a candidate for a future 16-kb/s speech coding standard. >

In this paper, we initiate a study on the deployment of large memories at the hardware and software design and implementation of a signal data acquisition system, making them essential tools for meeting the different needs of applications in signal acquisition system and not only can complete the data acquisition, storage, and read operations via VB-based interface software options, but also can change sampling rates. Furthermore, IMA-ADPCM speech coding algorithms is used and allows continuous recording of data, which is then stored in the system memory. The highly intelligent data gathering system which has the ability of high-precision real-time sampling, and it has merit in large storage capacity, power supply convenient, low-power, hot-swappable, portable, easy to operate, user-friendly, versatile, and good scalability. Experimental results show the system can achieve high signal to noise ratio of audio signal.

One of the important applications of underwater communication is speech transmission between two divers or between divers and ship or submarine. This paper describes a project designed to investigate and demonstrate underwater communication system in Persian Gulf for speech transmission in a real channel. At first, transmitter is designed, then channel with real data is simulated by neural network and at last receiver is designed. Transmitted data is speech signal that for more safety in transmission and low frequency bandwidth, a cryptography algorithm and speech coding algorithm is applied in transmitter. Quadrature phase shift keying (QPSK) signaling is employed to make efficient use of the available channel bandwidth. In the receiver, linear equalizer and decision feedback equalizer (DFE) are tested and the best of them is applied. Also ray tracing method is used for simulation of sound waves propagation in Persian Gulf underwater communication channel.

An improved version of the variable rate phonetic seg mentation (VRPS) algorithm for speech coding, applicable to CDMA digital cellular systems is presented. The coder performs activity detection to distinguish speech from background noise. Each frame of active speech is classifted into one of four phonetic categories. A distinct coding configuration and bit rate is applied to each category. The perceptual quality of the coded speech has been improved through the use of a new class-dependent adaptive postfiltering which attenuates the noise in the valleys of the speech spectrum. The robustness of the phonetic classffication algorithm in the presence of back ground vehicle noise has also been improved, by adapting classilier parameters using properties of the noise. These two modifications combine to improve the perceptual quality of the coder, while reducing the average rate by 300-450 b/s.

The authors present a novel image coding algorithm based on a class of image models known as doubly stochastic Gaussian models (DSGM). They exploit the nonhomogeneous nature of images by a space-variant autoregressive representation that switches in a set of linear predictive submodels. The switch is controlled by a 2-D Markov chain. The coder is a DPCM (differential pulse code modulation) system that is given the submodel (predictor) coefficients. In order to obtain these predictors, a recursive state estimation of the underlying Markov chain is done. This combination provides the doubly recursive prediction nature of this algorithm. Two coding schemes based on this structure are introduced. The first is a backward adaptation DPCM coder that needs very few side information bits. The other transmits codes for both model indices and quantized prediction residuals. Experimental results for different bit rates are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

In this paper, a Packet Loss Concealment (PLC) algorithm for ITU-G.722.2 speech coder is proposed in order to improve the decoded speech quality under burst packet loss conditions over packet-switched networks. First, we evaluated the repetition of the last received frame method in order to improve the concealment of lost frames. Then, we made a statistical study to evaluate the correlation between parameters values of adjacent frames. Finally, we present a new PLC method for ITU-G.722.2 by proposing an efficient approach to sending the side information to improve concealment of the lost frames and to resynchronize the encoder and decoder. The proposed method significantly improves the robustness of the ITU-G.722.2 codec against packet losses for voice over networks services. Tests in terms of Wideband Perceptual Evaluation of Speech Quality Mean Opinion Score (WB-PESQ MOS) quality measure and MUlti-Stimulus test with Hidden Reference and Anchor (MUSHRA) evaluation confirm the superiority of our proposed method against the PLC method embedded in G.722.2.

Bias field reduction by localized Lloyd–Max quantization

Optimal reconstruction from quantized data

Lattice low-delay vector excitation coding (LLD-VXC) is a speech coding system based on analysis-by-synthesis excitation coding and backward adaptation of the synthesis filter. The introduction of a lattice filter as a (high order) short-term predictor has significant advantages, such as fast tracking of speech signal nonstationarities, simple stability verification, and uniform distribution of the computational load. The objective of this paper is to present a Lattice LD-VXC (LLD-VXC) codec and experimental results obtained at rates of 8, 9.6, and 16 kb/s. A sign algorithm for lattice filter adaptation is introduced in order to reduce computational complexity